An economic study of controlled release urea and split applications of nitrogen as compared with non-coated urea under conventional and reduced tillage management
Bibliographic record
Abstract
Khakbazan, M., Grant, C. A., Finlay, G., Wu, R., Malhi, S. S., Selles, F., Clayton, G. W., Lupwayi, N. Z., Soon, Y. K. and Harker, K. N. 2013. An economic study of controlled release urea and split applications of nitrogen as compared with non-coated urea under conventional and reduced tillage management. Can. J. Plant Sci. 93: 523-534. To evaluate the use of controlled-release urea (CRU) as a beneficial management practice for nitrogen management of wheat, barley, and canola, a multi-location study was conducted from 2004 to 2006 in a range of agro-environments across western Canada. The objective was to evaluate the relative economic performance of CRU and non-coated urea (NCU) for their effects on seed yield and quality, costs and net revenue (NR) using conventional tillage (CT) and reduced tillage (RT) management under varying environmental conditions. The NR was estimated as the income remaining after paying for all cash costs, ownership costs on machinery and buildings, and labour. The main factor affecting crop yield and NR was N application rate. In general, application of NCU produced similar or higher net revenues than that of CRU, split fertilizer applications or a blend of NCU and CRU. There were some limited situations where the use of split applications, CRU or CRU in a blend with the NCU increased crop yield as compared with NCU; however, the increased yield was not sufficient to cover the extra costs of CRU or the split application. The impact of tillage system on crop yield and NR was not consistent. Net revenue was higher under CT than RT for certain crops in some regions, but not in all regions or for all crops. Overall, NR analysis indicated that use of CRU did not provide an economic benefit over the use of NCU.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".